# Reading the full dataset
GeneExpression <- readRDS("GE.Rdata")
GMTFileName <- "c5.go.bp.v7.5.1.symbols.gmt"
# selecting the samples we need
#GeneExpression <- GeneExpression[GeneExpression$samples$cell_type == "cd117",]
GeneExpression <- GeneExpression[GeneExpression$samples$lib.size > 100000,]
# setting up main parameters
FactorsList <- c("treatment")
# setting up parameters for GO analyses
CurrentFactor <- 1
FDRLimit <- 0.1
GeneSetOfInterest <- "GOBP_CEREBELLAR_CORTEX_FORMATION"
Normalization to middle line.
## Warning in brewer.pal(nlevels(col.group), "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
# Start of the model
ModelDesign <- model.matrix(~treatment, data = GeneExpression$samples)
ExpressionValues <- voom(GeneExpression, ModelDesign, plot = T)
ModelFit <- lmFit(ExpressionValues, ModelDesign) %>% eBayes
Result <- topTable(ModelFit, number = Inf, sort.by = "logFC")
## Removing intercept from test coefficients
#End of the model
## (Intercept) treatmentRBD
## RBD1 1 1
## RBD2 1 1
## RBD3 1 1
## WT1 1 0
## WT2 1 0
## WT3 1 0
## attr(,"assign")
## [1] 0 1
## attr(,"contrasts")
## attr(,"contrasts")$treatment
## [1] "contr.treatment"
## (Intercept) treatmentRBD
## Down 12 24
## NotSig 1464 19048
## Up 17675 79
## Warning in instance$preRenderHook(instance): It seems your data is too big
## for client-side DataTables. You may consider server-side processing: https://
## rstudio.github.io/DT/server.html
## Warning in brewer.pal(nlevels(col.group), "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Standard deviation Proportion of Variance Cumulative Proportion
## PC1 26.78295 0.29917 0.29917
## PC2 22.51462 0.21141 0.51057
## PC3 20.89927 0.18216 0.69274
## PC4 19.91570 0.16542 0.85816
## PC5 18.44207 0.14184 1.00000
## Warning: One or more parsing issues, see `problems()` for details
## Rows: 7658 Columns: 25
## -- Column specification --------------------------------------------------------
## Delimiter: "\t"
## chr (25): X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12, X13, X14, X15, ...
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Negative Positive
## 1 0 1
## 2 0 1
## 3 0 1
## 4 1 0
## 5 1 0
## 6 1 0
## attr(,"assign")
## [1] 1 1
## attr(,"contrasts")
## attr(,"contrasts")$GroupFactor
## [1] "contr.treatment"
## Contrasts
## Levels TreatmentEffect
## Negative -1
## Positive 1
## [1] "GO pathways analyzed: 7649"
## [1] "Affected GO pathways (Up + Down, FDR < 0.1 ): 0 + 0"
## Joining, by = "GO.ID"
Execution start time: 2022-02-14 12:41:49
Execution end time: 2022-02-14 12:42:35